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OpenAlex Citation Counts

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OpenAlex is a bibliographic catalogue of scientific papers, authors and institutions accessible in open access mode, named after the Library of Alexandria. It's citation coverage is excellent and I hope you will find utility in this listing of citing articles!

If you click the article title, you'll navigate to the article, as listed in CrossRef. If you click the Open Access links, you'll navigate to the "best Open Access location". Clicking the citation count will open this listing for that article. Lastly at the bottom of the page, you'll find basic pagination options.

Requested Article:

Imputing Satellite-Derived Aerosol Optical Depth Using a Multi-Resolution Spatial Model and Random Forest for PM2.5 Prediction
Behzad Kianian, Yang Liu, Howard H. Chang
Remote Sensing (2021) Vol. 13, Iss. 1, pp. 126-126
Open Access | Times Cited: 39

Showing 1-25 of 39 citing articles:

Addressing Biases in Ambient PM2.5 Exposure and Associated Health Burden Estimates by Filling Satellite AOD Retrieval Gaps over India
Varun Katoch, Alok Kumar, Fahad Imam, et al.
Environmental Science & Technology (2023) Vol. 57, Iss. 48, pp. 19190-19201
Closed Access | Times Cited: 17
Continuous mapping of fine particulate matter (PM<sub>2.5</sub>) air quality in East Asia at daily 6 × 6 km<sup>2</sup> resolution by application of a random forest algorithm to 2011–2019 GOCI geostationary satellite data
Drew C. Pendergrass, Shixian Zhai, Jhoon Kim, et al.
Atmospheric measurement techniques (2022) Vol. 15, Iss. 4, pp. 1075-1091
Open Access | Times Cited: 24
High resolution mapping of nitrogen dioxide and particulate matter in Great Britain (2003–2021) with multi-stage data reconstruction and ensemble machine learning methods
Arturo de la Cruz Libardi, Pierre Masselot, Rochelle Schneider, et al.
Atmospheric Pollution Research (2024) Vol. 15, Iss. 11, pp. 102284-102284
Open Access | Times Cited: 5
A Novel Evolutionary Deep Learning Approach for PM2.5 Prediction Using Remote Sensing and Spatial–Temporal Data: A Case Study of Tehran
Mehrdad Kaveh, Mohammad Saadi Mesgari, Masoud Kaveh
ISPRS International Journal of Geo-Information (2025) Vol. 14, Iss. 2, pp. 42-42
Open Access
Dynamic prediction of PM2.5 concertation in China using experience replay with multi-period memory buffers
Haoze Shi, Xin Yang, Hong Tang, et al.
Atmospheric Research (2025), pp. 108063-108063
Closed Access
Comparative Analysis of Two Machine Learning Algorithms in Predicting Site-Level Net Ecosystem Exchange in Major Biomes
Jianzhao Liu, Yunjiang Zuo, Nannan Wang, et al.
Remote Sensing (2021) Vol. 13, Iss. 12, pp. 2242-2242
Open Access | Times Cited: 29
Spatio-Temporal Characteristics of PM2.5 Concentrations in China Based on Multiple Sources of Data and LUR-GBM during 2016–2021
Hongbin Dai, Guangqiu Huang, Jingjing Wang, et al.
International Journal of Environmental Research and Public Health (2022) Vol. 19, Iss. 10, pp. 6292-6292
Open Access | Times Cited: 20
Spatiotemporal high-resolution imputation modeling of aerosol optical depth for investigating its full-coverage variation in China from 2003 to 2020
Qingqing He, Weihang Wang, Yimeng Song, et al.
Atmospheric Research (2022) Vol. 281, pp. 106481-106481
Open Access | Times Cited: 20
Satellite-based prediction of surface dust mass concentration in southeastern Iran using an intelligent approach
Seyed Babak Haji Seyed Asadollah, Ahmad Sharafati, Davide Motta, et al.
Stochastic Environmental Research and Risk Assessment (2023) Vol. 37, Iss. 10, pp. 3731-3745
Closed Access | Times Cited: 11
Data level and decision level fusion of satellite multi-sensor AOD retrievals for improving PM2.5 estimations, a study on Tehran
Ali Mirzaei, Hossein Bagheri, Mehran Sattari
Earth Science Informatics (2023) Vol. 16, Iss. 1, pp. 753-771
Closed Access | Times Cited: 10
Coupling the linear mixed effects model with random forest improves hourly PM2.5 estimation from Himawari-8 AOD over the Yangtze River Delta
Yunhui Tan, Quan Wang, Zhaoyang Zhang
Atmospheric Pollution Research (2023) Vol. 14, Iss. 5, pp. 101739-101739
Closed Access | Times Cited: 9
PM2.5 extended-range forecast based on MJO and S2S using LightGBM
Zhongqi Yu, Jinghui Ma, Yuanhao Qu, et al.
The Science of The Total Environment (2023) Vol. 880, pp. 163358-163358
Closed Access | Times Cited: 8
Estimation of historical daily PM2.5 concentrations for three Chinese megacities: Insight into the socioeconomic factors affecting PM2.5
Hongmei Xu, Yunlong Bai, Zezhi Peng, et al.
Atmospheric Pollution Research (2024) Vol. 15, Iss. 6, pp. 102130-102130
Closed Access | Times Cited: 2
A new hybrid deep neural network for multiple sites PM2.5 forecasting
Mengfan Teng, Siwei Li, Jie Yang, et al.
Journal of Cleaner Production (2024) Vol. 473, pp. 143542-143542
Closed Access | Times Cited: 2
Fast and operational gap filling in satellite-derived aerosol optical depths using statistical techniques
Kyunghwa Lee, Mijeong Kim, Myungje Choi, et al.
Journal of Applied Remote Sensing (2022) Vol. 16, Iss. 04
Open Access | Times Cited: 11
Application of Machine-Learning-Based Fusion Model in Visibility Forecast: A Case Study of Shanghai, China
Zhongqi Yu, Yuanhao Qu, Yunxin Wang, et al.
Remote Sensing (2021) Vol. 13, Iss. 11, pp. 2096-2096
Open Access | Times Cited: 15
Revealing dominant patterns of aerosols regimes in the lower troposphere and their evolution from preindustrial times to the future in global climate model simulations
Jingmin Li, Mattia Righi, Johannes Hendricks, et al.
(2024)
Open Access | Times Cited: 1
Can satellite data on air pollution predict industrial production?
Jean‐Charles Bricongne, Baptiste Meunier, Thomas Pical
SSRN Electronic Journal (2021)
Closed Access | Times Cited: 11
Effect of Feature Selection on the Prediction Model of FeO Content in Sinter
Jiahao Xi, Xiangdong Xing, Zhaoying Zheng, et al.
JOM (2023) Vol. 75, Iss. 12, pp. 5930-5939
Closed Access | Times Cited: 3
Multivariate spatial prediction of air pollutant concentrations with INLA
Wenlong Gong, Brian J. Reich, Howard H. Chang
Environmental Research Communications (2021) Vol. 3, Iss. 10, pp. 101002-101002
Open Access | Times Cited: 7
A high-resolution computationally-efficient spatiotemporal model for estimating daily PM2.5 concentrations in Beijing, China
Yiran Lyu, Kipruto Kirwa, Michael T. Young, et al.
Atmospheric Environment (2022) Vol. 290, pp. 119349-119349
Closed Access | Times Cited: 4
Reconstructing aerosol optical depth using spatiotemporal Long Short-Term Memory convolutional autoencoder
Lü Liang, Jacob Daniels, Michael Biancardi, et al.
Scientific Data (2023) Vol. 10, Iss. 1
Open Access | Times Cited: 2
Data Assimilation of AOD and Estimation of Surface Particulate Matters over the Arctic
Kyung Man Han, Chang Hoon Jung, Rae‐Seol Park, et al.
Applied Sciences (2021) Vol. 11, Iss. 4, pp. 1959-1959
Open Access | Times Cited: 5
Fuzzy-based missing value imputation technique for air pollution data
Ayon Mustafi, Asif Iqbal Middya, Sarbani Roy
Artificial Intelligence Review (2022) Vol. 56, Iss. 2, pp. 1-38
Closed Access | Times Cited: 3
Comment on egusphere-2024-1024
Jingmin Li, Mattia Righi, J. E. Hendricks, et al.
(2024)
Open Access
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